What is packt-netops-ai-workshop AGENTS.md?

Workshop instructions for teaching network engineers to automate network tasks with AI, using Containerlab to run virtual network devices, Ansible to configure them, MCP servers to connect tools, and Prometheus to observe them.

Use them when setting up the workshop, deploying or removing Containerlab topologies, running Ansible playbooks, or testing the network MCP server.

They provide the setup checks and lab commands needed to reproduce the workshop environment and operate its example networks.

How wcollins/packt-netops-ai-workshop configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to wcollins/packt-netops-ai-workshop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/wcollins/packt-netops-ai-workshop/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/wcollins/packt-netops-ai-workshop

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/wcollins/packt-netops-ai-workshop/agents-md/github.svg)](https://agentmods.dev/instructions/wcollins/packt-netops-ai-workshop/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/wcollins/packt-netops-ai-workshop/agents-md"><img src="https://agentmods.dev/badge/instructions/wcollins/packt-netops-ai-workshop/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/wcollins/packt-netops-ai-workshop/agents-md"><img src="https://agentmods.dev/badge/instructions/wcollins/packt-netops-ai-workshop/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,070 This file is loaded in full into every session.

When invoked 1,070 The same file — it is already loaded in full.

Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.01070	$0.01070
Opus 5.5	$0.00428	$0.00428
Sonnet 5.5	$0.00214	$0.00214
Haiku 4.5	$0.00107	$0.00107

Measured 2mo ago against content hash e1347ce52fa2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

packt-netops-ai-workshop AGENTS.md scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo containerlab deploy -t topology.clab.yml # Deploy network

AGENTS.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

A three-part workshop teaching network engineers to leverage AI and LLMs for network automation. Built around Containerlab with Arista cEOS switches, Ansible automation, Model Context Protocol (MCP) servers, and Prometheus observability.

Commands

Environment Setup

uv sync                                      # Install dependencies
./scripts/verify-setup.sh                    # Verify prerequisites

Lab 1 - Containerlab

cd lab-01-copilots
sudo containerlab deploy -t topology.clab.yml      # Deploy network
sudo containerlab destroy -t topology.clab.yml     # Teardown network

Lab 1 - Ansible

cd lab-01-copilots/ansible
source .venv/bin/activate
ansible-playbook playbooks/01-interfaces.yml -i inventories/clab.yml
ansible-playbook playbooks/04-set-interfaces.yml -i inventories/clab.yml \
  --extra-vars "target_host=leaf1 interface_name=Ethernet3 description='New Link' ip_address=10.0.0.1/30"

Lab 2 - MCP Server

cd lab-02-mcp-server
mcp dev network_mcp_server.py                # Test in MCP Inspector
mcp run network_mcp_server.py                # Run for Claude Desktop
mcp run -t sse network_mcp_server.py         # Run for remote access

Lab 3 - Observability Stack

cd lab-03-observability
docker compose up -d                         # Start Prometheus + Grafana
docker compose down                          # Stop stack

Testing & Quality

python -m pytest lab-02-mcp-server/tests/ -v  # Run tests
ruff check .                                   # Lint
mypy lab-02-mcp-server/                        # Type check

Architecture

Network Topology

Spines (2): spine1, spine2 - AS65100, IPs 198.18.1.11-12
Leaves (4): leaf1-4 - AS65101-65104, IPs 198.18.1.21-24
BGP spine-leaf fabric with point-to-point links

Lab Structure

Lab 1 (lab-01-copilots/): Ansible playbook development with Claude Code

ansible/playbooks/01-03.yml: Base configs for spine1 + leaf1
ansible/playbooks/01.5-03.5.yml: Extended configs for remaining devices
ansible/playbooks/04-09.yml: Single-operation playbooks for MCP integration
prompts/: Claude Code prompts for extending playbooks

Read the full file on GitHub · 121 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 121 lines · 1,070 tokens per session scan B e1347ce52fa2

Subscribe to this mod's changes

packt-netops-ai-workshop AGENTS.md is an instructions file published in the GitHub repository wcollins/packt-netops-ai-workshop (30 stars, last pushed 8mo ago), licensed MIT. It adds 1,070 tokens to every session, about $0.0043 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Containers DevOps and cloud LLM Learning and teaching ai ai-agents ansible copilot mcp

packt-netops-ai-workshop AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
packt-netops-ai-workshop AGENTS.mdwcollins/packt-netops-ai-workshop	Instructions file	30	8mo ago	MIT	B	1,070	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

packt-netops-ai-workshop: Instructions file for Codex